Search Results (1,198)

Rivers are a key pathway for the transport of plastics into the ocean. Studies of plastic pollution in Arctic rivers remain limited due to the inaccessibility of sampling sites and work in extreme weather conditions. This work presents the results of a three-year (2019–2021) survey of floating large microplastics (0.5–5 mm) and meso/macroplastics (>5 mm) in the Northern Dvina River, an actively navigated river that drains a densely populated region into the White Sea. Sampling was conducted during the ice-free periods (May–October) along a ∼3.5 km transect using a Neuston net, providing a multi-year dataset spanning three ice-free seasons. A critical methodological advancement was the calculation of plastic river–sea flux using the discharge of the sampled surface layer (upper 20 cm), which constitutes only ∼3% of the river’s total discharge, rather than the total discharge itself. Observed microplastic concentrations (average 0.003 items ${\mathrm{m}}^{-3}$) were low compared to many European rivers, and lower than those reported in the adjacent Barents and Kara Seas. Microplastic abundance was significantly lower during the high-water season than during the low-water season, which resulted in practically no seasonal variability in microplastic fluxes from the river to the White Sea (average 0.3 items ${\mathrm{s}}^{-1}$). A notable finding was that in some cases, meso/macroplastics outnumbered microplastics by item count, underscoring the river’s role as a significant source of larger plastic debris. A geospatial assessment of Arctic rivers’ pollution potential was performed, using socio-economic indicators such as near-delta population density and port activity. This study identified the Northern Dvina River as a major contributor of microplastics among the Arctic rivers. Full article

Silver-coated copper (Cu@Ag) core–shell nanoparticles are promising interconnect materials for electronic packaging due to their high conductivity, oxidation resistance, and reduced use of precious metals. However, the key factors governing their sintering behavior and mechanical performance are not fully understood. In this study, molecular dynamics simulations were performed to examine the effects of sintering pressure (300–700 MPa), temperature (500–700 K), particle size, and silver shell thickness on atomic diffusion, microstructural evolution, and mechanical properties. Results show that higher pressure improves particle contact, accelerates densification, and strengthens interfacial bonding, with optimal performance achieved at 600–700 MPa. Elevated temperatures enhance atomic mobility, promoting neck growth and pore elimination, with the most active diffusion observed between 650 K and 700 K. Particle size and shell thickness also affect sintering: the Ag6Cu3 configuration exhibits the highest atomic mobility and a balanced combination of strength and ductility. Moderately thick silver shells facilitate surface diffusion and interfacial interdiffusion, while mechanisms such as the Kirkendall effect and local plastic relaxation reduce defect density, yielding stable sintered structures. These findings provide atomic-scale insights into the sintering mechanisms of Cu@Ag nanoparticle solder pastes and offer guidance for optimizing processing parameters in high-performance electronic packaging applications. Full article

Foreign plastic objects (FPOs) in poultry products present significant food safety risks and cause economic losses for the industry. Conventional detection methods, including X-rays and color imaging, often struggle to identify small or low-density plastics. Hyperspectral imaging (HSI) offers both spatial and spectral information but suffers from high computational cost when applied for FPO identification in industrial environments. This study introduces a parameter-efficient and computationally efficient spatial–spectral transformer framework for pixel-level classification of FPOs on broiler meat using NIR-HSI (1000–1700 nm). The framework integrates three innovations: (1) center-focused linear attention (CFLA) to reduce computational complexity from $O\left(n^2\right)$ to $O\left(n\right)$; (2) patch-local mixed-axis 2D rotary position embedding to preserve geometric relationships within hyperspectral patches; and (3) low-rank factorized projection (LRP) matrices to reduce parameters by approximately 50% within projection weight matrices. The framework was trained and evaluated on a dataset of 52 chicken fillets, comprising 295,340 labeled target hyperspectral pixels from 12 common polymer types and 1 fillet class. The model achieved 99.39% overall accuracy, 99.57% average accuracy, and a 99.31 Kappa coefficient across 248,540 test pixels. Per-class precision, recall, and F1-score exceeded 98.05%, 98.59%, and 98.76%, respectively, across all classes. Efficiency analyses showed an 83% reduction in multiply–accumulate operations (MACs), a 22% reduction in trainable parameters, and a model size reduction from 1.72 MB to 1.35 MB relative to the baseline configuration. These gains also translated into practical inference benefits, with the final model achieving a throughput of 212,971.5 hyperspectral patch cubes/s and a 4.19× speedup over the baseline. These results demonstrate that the proposed framework combines strong classification performance with high efficiency, supporting high-throughput inference for real-time monitoring and enabling contamination source traceability and preventive quality control in industrial poultry processing. The approach provides a benchmark for applying transformer-based models to food safety inspection tasks. Full article

To address the problems of coarse grains and unsatisfactory mechanical properties of as-cast Mg-8.5Al-1Zn alloy, which hinder its application in dissolvable bridge plugs, this study took the alloy as the research object and subjected it to plastic deformation via hot extrusion with an extrusion ratio of 12. Through the use of Combined Electron Backscatter Diffraction (EBSD) and Transmission Electron Microscopy (TEM) Testing and Characterization Techniques, the macroscopic mechanical properties, microstructural evolution, and extrusion deformation mechanism of the alloy in both as-cast and as-extruded states were systematically investigated. The results indicate that hot extrusion deformation significantly enhances the comprehensive mechanical properties of the alloy. Compared with the as-cast alloy, the tensile strength, yield strength, and elongation of the as-extruded alloy are increased by 104.0%, 314.9%, and 166.7%, respectively, with the static toughness increasing by 809.1%. The as-cast alloy exhibits coarse grains, Al element segregation, and high-density dislocations. After hot extrusion, dynamic recrystallization dominates the grain refinement, reducing the grain size by approximately 60%. Solute atoms precipitate to form multiphase structures and coherent nano-scale precipitates, along with the formation of tensile twins and a weakened bimodal texture. The improved yield strength of the as-extruded alloy stems from the synergistic effect of multiple strengthening mechanisms, among which precipitation strengthening induced by nano-precipitates is the primary contributor. The enhanced plasticity is attributed to grain refinement and texture regulation. This study clarifies the extrusion deformation mechanism of the Mg-8.5Al-1Zn alloy for dissolvable bridge plugs and verifies the rationality of the hot extrusion process with an extrusion ratio of 12, providing technical support for its industrial application in dissolvable bridge plugs and the performance regulation of similar dissolvable magnesium alloys. Full article

The low absolute strength and insufficient room-temperature ductility remain key bottlenecks that restrict the engineering application of magnesium alloys in high-end industrial fields. In the present study, 1 vol.% carbon nanotubes (CNTs)-reinforced Mg-xAl (x = 0, 1, and 1.5 wt.%) composites were synthesized via a powder metallurgy route coupled with hot extrusion–rolling processing to realize a simultaneous improvement in mechanical properties. The hot extrusion–rolling processed 1 vol.% CNTs/Mg-1Al composite exhibits an ultimate tensile strength of 300 MPa and an elongation to failure of 9%, showing an excellent strength–ductility synergy. Microstructural characterization reveals a well-bonded interface between CNTs and the Mg matrix. Deformation incompatibility between CNTs and the magnesium matrix during hot extrusion–rolling induces a high density of dislocations, providing an important strengthening contribution. Moreover, an increased proportion of low-angle grain boundaries and the development of a bimodal texture promote significant grain refinement and effectively activate non-basal slip systems, thereby alleviating plastic deformation constraints. The synergistic effects of interfacial strengthening, dislocation strengthening, grain boundary strengthening, and texture regulation together contribute to the simultaneous improvement of strength and ductility in CNTs-reinforced Mg-Al composites. Full article

The effects of progressive drought stress were examined in four economically important plant species belonging to the Lamiaceae family: catnip (Nepeta cataria L.), lavender (Lavandula angustifolia Mill.), holy basil (Ocimum tenuiflorum L.), and perilla mint (Perilla frutescens (L.) Britton). Plants were grown in a controlled pot experiment under three soil water capacity levels: 70% (control), 50% (moderate stress), and 30% (severe stress), and the drought stress lasted for 30 days. The study evaluated a comprehensive set of leaf micromorphological parameters, including the density and diameter of glandular trichomes, stomatal density and size, and the thickness of the lamina, mesophyll, epidermis, cuticle, and parenchymal layers. In addition, essential oil (EO) content, total flavonoid content (TFC), and elemental composition were analyzed. Drought responses were strongly species-specific. O. tenuiflorum, P. frutescens, and N. cataria showed high sensitivity characterized by reduced biomass and thinning of leaf tissues. These changes were accompanied by typical xeromorphic adaptations, such as increased stomatal and glandular trichome density, and reduced stomatal size. L. angustifolia exhibited pronounced cuticle thickening, suggesting an effective structural mechanism to minimize water loss. Secondary metabolism also responded differently among species. In some cases, drought shifted metabolic allocation toward flavonoid accumulation at the expense of essential oils, whereas in others, moderate stress promoted the co-accumulation of both compounds. These patterns indicate distinct adaptive strategies linking anatomical plasticity with metabolic regulation. Overall, moderate drought supported adaptive responses, while severe water limitation impaired growth and metabolic production. From a practical perspective, maintaining moderate soil water availability appears critical to optimize both plant performance and the accumulation of valuable secondary metabolites in Lamiaceae species. Full article

Temperature is a major determinant of plant metabolic plasticity, yet its role in directing volatile and semi-volatile specialized metabolism in Ginkgo biloba remains poorly understood. In this study, we investigated how contrasting low- and high-temperature treatments reshape secondary metabolite contents in G. biloba microclones cultivated in vitro. Plants were exposed to cold (+3 °C) and heat (+30 °C) conditions, and their responses were analyzed using GC–MS profiling, anatomical measurements, chlorophyll fluorescence, and multivariate statistics. Cold treatment selectively increased the abundances of monoterpenes (13.22%) and sesquiterpenes (13.83%), with the strongest accumulation of caryophyllene, eucalyptol, and (1S)-camphor. In contrast, heat treatment reduced ester content to 3.73% and strongly enriched oxy-sesquiterpenes (46.50%) and lactone/ketone/spiroketone (29.54%) contents. The enhanced accumulation of isocalamendiol, isoshyobunone, cyclohexanone derivative, dehydroxy-isocalamendiol, and (+)-2-bornanone was observed under heat. According to the multivariate analysis, control plants were associated with traits reflecting optimal physiological performance, including greater parenchyma, phloem, and xylem thickness, larger vascular bundles, longer stomata, and higher NPQ, qN, Y(NPQ), and F_v/F_m. Cold-treated plants showed thicker epidermis and sclerenchyma, higher stomatal density and width, elevated Y(NO), and an enrichment of esters and terpenoids, whereas heat-treated plants were characterized by thicker adaxial and abaxial epidermis, increased mesophyll thickness, and higher levels of oxygenated metabolites. These findings expand current knowledge beyond terpene trilactones and flavonoids and identify Ginkgo microclones as a useful in vitro model for temperature-guided metabolic reprogramming and targeted metabolite enrichment. Full article

The proliferation of intelligent edge devices demands compact, low-power hardware capable of dynamically switching between sensing, logic, and learning tasks—a versatility that traditional multi-chip solutions fundamentally lack. Here, we demonstrate a reconfigurable spin–orbit torque (SOT) device based on an FeTb/Ru/Co synthetic antiferromagnetic (SAF) heterostructure. By modulating the input current amplitude, the device dynamically switches between two distinct operating modes: saturation and activation. In the saturation regime (>80 mA), deterministic magnetization reversal enables Boolean logic operations (AND, NOR). In the activation regime (<80 mA), gradual, non-volatile conductance modulation emulates synaptic plasticity. Benefiting from the strong antiferromagnetic coupling and near-zero net magnetization of the SAF structure, all operations are achieved without external magnetic fields. This single-device, dual-mode reconfigurable architecture establishes a new paradigm for high-density, low-power, multifunctional in-memory computing units, with promise for advancing adaptive edge computing chips. Full article

Plastic pyrolysis is widely used to treat polyolefin-rich waste; however, wax byproducts generated during these processes are typically regarded as low-value intermediates. Here, a byproduct-compatible upcycling strategy is proposed to convert polyethylene (PE) pyrolysis wax into activated carbon, enabling integration of functional carbon production into existing recycling value chains. Thermal oxidation was employed to stabilize the wax prior to carbonization, and stabilization at 300 °C yielded a mechanically stable precursor with a high carbon yield. Subsequent carbonization and KOH activation at 900 °C produced an activated carbon (PEWax_AC) with a specific surface area of 1704 m²/g, exceeding that of a representative commercial activated carbon (1575 m²/g). Microstructural analysis revealed predominantly amorphous carbon with locally ordered domains. In symmetric supercapacitor cells, PEWax_AC exhibited higher capacitance at low rates and superior rate capability at high scan rates and current densities, along with reduced charge-transfer resistance. Specifically, PEWax_AC delivered a specific capacitance of 22.9 F/g at 5 mV/s and exhibited a rate retention of 18.6% from 0.1 to 7.0 A/g. These findings demonstrate that plastic pyrolysis wax is a viable and scalable carbon precursor for high-performance supercapacitor electrodes. Full article

In recent years, plastic recycling has emerged as a critical concern in environmental protection and waste management. Among the various techniques for repurposing plastic waste into valuable products, extrusion of filaments for 3D printing has proven to be a highly effective method. A thorough understanding of the crystallization behavior of recycled plastics used in 3D printing is essential, as it significantly influences their final performance. This review provides an in-depth analysis of the crystallization behavior and crystallinity of recycled semi-crystalline polymers, with particular emphasis on recycled commodity plastics such as recycled polyethylene terephthalate (rPET), recycled polypropylene (rPP), and recycled high-density polyethylene (rHDPE). Recent research published between 2015 and 2025 was systematically synthesized and provides information on sources of plastic waste, additives employed, and recycling processes involved, with the findings summarized in a table that highlights their effects on polymer crystallinity. Furthermore, the key factors impacting the crystallinity of 3D-printed recycled plastics were examined, including the influence of additives, multiple processing cycles, printing parameters, and thermal treatments. Research gaps and the challenges faced during the printing process were also identified and discussed. By consolidating recent findings, this review provides a comprehensive understanding of the crystallization behavior of recycled plastics in 3D printing, thereby providing guidance for future research and developing strategies to optimize the performance of these materials. Full article

Plastic pollution poses a major environmental threat to coastal ecosystems, particularly in enclosed and semi-enclosed seas where limited water exchange promotes debris accumulation. This study presents a high-resolution spatial analysis of coastal plastic debris along the Khachmaz coastline in the western Caspian Sea. The analysis integrates unmanned aerial vehicle (UAV) imagery, YOLO-based deep learning detection, and spatial statistical methods. High-resolution UAV orthophotos enabled the automated detection of individual plastic debris items, which were converted into spatial point data for further analysis. Spatial patterns were assessed using areal density estimation, nearest neighbor analysis, kernel density estimation, and Ripley’s L-function to examine clustering across multiple spatial scales. A total of 2389 plastic debris items were identified within 0.0439 km², corresponding to an average density of 54,382 items per km². The results show that plastic debris is unevenly distributed, forming distinct clusters with four primary accumulation hotspots. Significant clustering occurs at spatial scales up to 20 m, with the strongest aggregation observed at distances below 5 m. Spatial overlay analysis indicates a strong association between plastic debris, reed-dominated coastal vegetation, and proximity to the shoreline, suggesting the potential role of localized retention processes and shoreline dynamics in debris accumulation. The combined use of UAV-based deep learning and spatial statistical analysis provides an integrated application framework for monitoring coastal plastic debris and supports targeted, sustainability-oriented coastal management strategies in the Caspian Sea region. Full article

Distributed recycling of high-density polyethylene (HDPE) into filament for use in material extrusion 3D printing has been proposed as part of a circular economy. There is a gap in the understanding of the potential for HDPE to release contaminants that are potentially hazardous to human health during reuse. Herein, HDPE from post-consumer packaging waste was sorted into food and non-food (NF) streams and virgin HDPE was taken as a benchmark material. All materials were extruded into filaments and recycled multiple times while monitoring emissions. In general, particle and organic chemical emissions decreased by 93 to 99% and 73 to 99%, respectively, with increased reprocessing cycle without appreciable decline in mechanical (Young’s modulus decreased by 5 to 16%), processability (melt flow index stable from 0.2 to 0.7 g/10 min for waste plastics), and thermal properties (crystallinity ranged from a 6% decrease to a 9% increase) of plastics. An exception was a sub-stream of NF plastic that had increased particle emissions (up to 3100%) with reprocessing cycle. Reductions in emissions during filament extrusion appeared to be more influenced by reprocessing cycle than by any specific process step (grinding, etc.). The progressive decline in emissions without appreciable loss of polymer integrity could be exploited to pre-condition HDPE to reduce potential hazardous emissions prior to extruding into filament. This work helps fill the knowledge gap on approaches to recycling plastics in distributed settings such as home-based businesses, which is critical for developing effective recommendations for controls to enable safe work practices such as the use of ventilation to minimize exposures. Full article

The advancement of artificial intelligence and information technologies has presented higher demands on neuromorphic computing information devices, entailing the emergence of next-generation devices. Polyoxometalates (POMs) are emerging as promising molecular nanomaterials for next-generation neuromorphic computing, providing distinct advantages over conventional metal oxides. In contrast to bulk oxides that suffer from stochastic filament formation and device-to-device variability, POMs possess atomically precise structures with discrete, multi-electron redox states that enable highly reproducible and deterministic resistive switching. Their molecular nature allows for stable, multi-level data representation through stepwise reduction in metal centers (e.g., V, W, Mo) and the emulation of essential synaptic plasticity functions. Furthermore, the exceptional structural and chemical tunability of POMs favors covalent or supramolecular functionalization, enabling precise engineering of the POM-electrode interface and controlled self-assembly on surfaces. This molecular precision not only addresses the scalability challenges of traditional memristors but also unlocks unique functionalities, such as multimodal switching coupled with visible chromic response for state visualization. Taking the advantages of intermolecular crosstalk and countercation dynamics, POM-based networks offer a pathway toward constructing three-dimensional neuronal architectures, effectively connecting molecular redox chemistry to advanced high-density neuromorphic computing paradigms. Full article

Active suspension systems are gaining growing attention in the automotive industry. This trend aligns with vehicle electrification and X-by-wire technologies adoption, also answering to the increasingly stringent requirements for passenger comfort and safety. Among the possible solutions, electromechanical actuators represent a valid alternative to traditional shock absorbers, integrating an electric machine that can be easily controlled to deliver the desired forces in both active and passive operations. The present work aims at developing an innovative transmission compound for a rotary electromagnetic active suspension system that is able to obtain high level NVH and safety performances. Two different proposed systems are analyzed. The first one couples a cycloidal transmission stage to a polymeric planetary one, while the second one couples the same cycloidal stage to a concentric magnetic gearbox. Both of them are expected to improve the NVH performances of the shock absorber, thanks to the high efficiency of the cycloidal reducer and to the properties of plastic materials and of magnetic coupling. The proposed systems are analyzed analytically and in simulation environment, providing promising results in terms of efficiency and torque density. Full article

The trade-off between strength and ductility remains a pivotal challenge in the development of multi-principal element alloys (MPEAs) for structural applications. Here, we report a dual-scale ordering strategy to achieve triple strengthening in a Ni-26.6Co-18.4Cr-5.4Nb-4.1Mo-2.3Al-0.3Ti-0.05Y (wt.%) MPEA through the synergistic interplay of L1₂ nanoprecipitates and local chemical order (LCO). The alloy was processed via cold rolling followed by aging at 750 °C for 8 h, resulting in a high density of coherent L1₂ precipitates (average size 47 ± 1 nm, volume fraction ~27%) with an ultra-low lattice misfit of 0.5%. Additionally, sub-nanoscale LCO domains with an average diameter of 0.62 nm were identified within the face-centered cubic matrix. This hierarchical microstructure yields an exceptional combination of mechanical properties at room temperature: yield strength of 1480 ± 6 MPa, ultimate tensile strength of 1678 ± 10 MPa, and a total elongation of 13.9 ± 0.2%. Quantitative strengthening analysis reveals that precipitation strengthening (697 MPa) is the dominant contributor, followed by dislocation strengthening (397 MPa). Transmission electron microscopy characterization of deformed samples reveals that the low stacking fault energy, promoted by LCO, facilitates the dissociation of perfect dislocations and the formation of extensive stacking faults. The intersection of stacking faults on different {111} planes generates a large number of Lomer–Cottrell locks, which significantly enhance work hardening and delay plastic instability. The findings demonstrate that engineering dual-scale ordered structures offers a promising pathway for developing MPEAs with a superior strength-ductility combination. Full article